Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models
Descripción del Articulo
The respiratory metabolism of fruits is affected by multiple internal (product) and external (environmental) factors that often interact with each other. Among the external factors that have the greatest influence on respiration are temperature, air composition, moisture content and illumination. Th...
| Autores: | , , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2020 |
| Institución: | Universidad Nacional de Trujillo |
| Repositorio: | Revista UNITRU - Scientia Agropecuaria |
| Lenguaje: | inglés |
| OAI Identifier: | oai:ojs.revistas.unitru.edu.pe:article/2801 |
| Enlace del recurso: | http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801 |
| Nivel de acceso: | acceso abierto |
| Materia: | respiration rate time series dynamic regression model exogenous variables transfer function. |
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Revista UNITRU - Scientia Agropecuaria |
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Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression modelsPérez-López, ArtemioRamírez-Guzmán, MarthaEspinosa-Solares, TeodoroAguirre-Mandujano, EleazarVillaseñor-Perea, Carlosrespiration ratetime seriesdynamic regression modelexogenous variablestransfer function.The respiratory metabolism of fruits is affected by multiple internal (product) and external (environmental) factors that often interact with each other. Among the external factors that have the greatest influence on respiration are temperature, air composition, moisture content and illumination. The aim of this paper is to elucidate the influence of environmental factors on the respiration rate of peach fruits based on transfer models obtained by dynamic regression modelling (ARIMAX). The fitted ARIMA models met the criteria of parsimony and white noise in residuals. The estimated coefficients of each model were statistically significant under the Durbin-Watson (DW), Akaike (AIC) and Schwarz (SBC) criteria. Transfer functions revealed 0.15% and 1.9% increase, and 0.001% decrease in the respiration rate of the peach fruit for each unit of change in temperature, relative humidity and illumination of the storage environment, respectively. The respiration rate response took place 1-8 minutes after the change in environmental variables had occurred. It was concluded that the dynamic regression modelling is reliable for predicting the physiological response of fruits the effect of external factors imposed continuously during postharvest handling.Universidad Nacional de Trujillo2020-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/280110.17268/sci.agropecu.2020.01.03Scientia Agropecuaria; Vol. 11 No. 1 (2020): Enero-Marzo; 23-29Scientia Agropecuaria; Vol. 11 Núm. 1 (2020): Enero-Marzo; 23-292306-67412077-9917reponame:Revista UNITRU - Scientia Agropecuariainstname:Universidad Nacional de Trujilloinstacron:UNITRUenghttp://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801/2875http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801/3167Derechos de autor 2020 Scientia Agropecuariainfo:eu-repo/semantics/openAccess2021-06-01T15:35:30Zmail@mail.com - |
| dc.title.none.fl_str_mv |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| title |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| spellingShingle |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models Pérez-López, Artemio respiration rate time series dynamic regression model exogenous variables transfer function. |
| title_short |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| title_full |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| title_fullStr |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| title_full_unstemmed |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| title_sort |
Postharvest respiration of fruits and environmental factors interaction: An approach by dynamic regression models |
| dc.creator.none.fl_str_mv |
Pérez-López, Artemio Ramírez-Guzmán, Martha Espinosa-Solares, Teodoro Aguirre-Mandujano, Eleazar Villaseñor-Perea, Carlos |
| author |
Pérez-López, Artemio |
| author_facet |
Pérez-López, Artemio Ramírez-Guzmán, Martha Espinosa-Solares, Teodoro Aguirre-Mandujano, Eleazar Villaseñor-Perea, Carlos |
| author_role |
author |
| author2 |
Ramírez-Guzmán, Martha Espinosa-Solares, Teodoro Aguirre-Mandujano, Eleazar Villaseñor-Perea, Carlos |
| author2_role |
author author author author |
| dc.subject.none.fl_str_mv |
respiration rate time series dynamic regression model exogenous variables transfer function. |
| topic |
respiration rate time series dynamic regression model exogenous variables transfer function. |
| dc.description.none.fl_txt_mv |
The respiratory metabolism of fruits is affected by multiple internal (product) and external (environmental) factors that often interact with each other. Among the external factors that have the greatest influence on respiration are temperature, air composition, moisture content and illumination. The aim of this paper is to elucidate the influence of environmental factors on the respiration rate of peach fruits based on transfer models obtained by dynamic regression modelling (ARIMAX). The fitted ARIMA models met the criteria of parsimony and white noise in residuals. The estimated coefficients of each model were statistically significant under the Durbin-Watson (DW), Akaike (AIC) and Schwarz (SBC) criteria. Transfer functions revealed 0.15% and 1.9% increase, and 0.001% decrease in the respiration rate of the peach fruit for each unit of change in temperature, relative humidity and illumination of the storage environment, respectively. The respiration rate response took place 1-8 minutes after the change in environmental variables had occurred. It was concluded that the dynamic regression modelling is reliable for predicting the physiological response of fruits the effect of external factors imposed continuously during postharvest handling. |
| description |
The respiratory metabolism of fruits is affected by multiple internal (product) and external (environmental) factors that often interact with each other. Among the external factors that have the greatest influence on respiration are temperature, air composition, moisture content and illumination. The aim of this paper is to elucidate the influence of environmental factors on the respiration rate of peach fruits based on transfer models obtained by dynamic regression modelling (ARIMAX). The fitted ARIMA models met the criteria of parsimony and white noise in residuals. The estimated coefficients of each model were statistically significant under the Durbin-Watson (DW), Akaike (AIC) and Schwarz (SBC) criteria. Transfer functions revealed 0.15% and 1.9% increase, and 0.001% decrease in the respiration rate of the peach fruit for each unit of change in temperature, relative humidity and illumination of the storage environment, respectively. The respiration rate response took place 1-8 minutes after the change in environmental variables had occurred. It was concluded that the dynamic regression modelling is reliable for predicting the physiological response of fruits the effect of external factors imposed continuously during postharvest handling. |
| publishDate |
2020 |
| dc.date.none.fl_str_mv |
2020-04-01 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801 10.17268/sci.agropecu.2020.01.03 |
| url |
http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801 |
| identifier_str_mv |
10.17268/sci.agropecu.2020.01.03 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801/2875 http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/2801/3167 |
| dc.rights.none.fl_str_mv |
Derechos de autor 2020 Scientia Agropecuaria info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Derechos de autor 2020 Scientia Agropecuaria |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad Nacional de Trujillo |
| publisher.none.fl_str_mv |
Universidad Nacional de Trujillo |
| dc.source.none.fl_str_mv |
Scientia Agropecuaria; Vol. 11 No. 1 (2020): Enero-Marzo; 23-29 Scientia Agropecuaria; Vol. 11 Núm. 1 (2020): Enero-Marzo; 23-29 2306-6741 2077-9917 reponame:Revista UNITRU - Scientia Agropecuaria instname:Universidad Nacional de Trujillo instacron:UNITRU |
| reponame_str |
Revista UNITRU - Scientia Agropecuaria |
| collection |
Revista UNITRU - Scientia Agropecuaria |
| instname_str |
Universidad Nacional de Trujillo |
| instacron_str |
UNITRU |
| institution |
UNITRU |
| repository.name.fl_str_mv |
-
|
| repository.mail.fl_str_mv |
mail@mail.com |
| _version_ |
1701379323159642112 |
| score |
13.987529 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).